全局优化的Fourier有限差分偏移方法研究

Seismic exploration is the main method of seeking oil and gas. With the development of seismic exploration, the target becomes more and more complex, which leads to a higher demand for the accuracy and efficiency in seismic exploration. Fourier finite-difference (FFD) method is one of the most valuable methods in complex structure exploration, which has obtained good effect. However, in complex media with wider angles, the effect of FFD method is not satisfactory. Based on the FFD operator, we extend the two coefficients to be optimized to four coefficients, then optimize them globally using simulated annealing algorithm. Our optimization method select the solution of one-way wave equation as the objective function. Except the velocity contrast, we consider the effects of both frequency and depth interval. The proposed method can improve the angle of FFD method without additional computation time, which can reach 75° in complex media with large lateral velocity contrasts and wider propagation angles. In this thesis, combinating the FFD method and alternative-direction-implicit plus interpolation(ADIPI） method, we obtain 3D FFD with higher accuracy. On the premise of keeping the efficiency of the FFD method, this method not only removes the azimuthal anisotropy but also optimizes the FFD mehod, which is helpful to 3D seismic exploration. We use the multi-parameter global optimization method to optimize the high order term of FFD method. Using lower-order equation to obtain the approximation effect of higher-order equation, not only decreases the computational cost result from higher-order term, but also obviously improves the accuracy of FFD method. We compare the FFD, SAFFD（multi-parameter simulated annealing globally optimized FFD）, PFFD, phase-shift method(PS）, globally optimized FFD （GOFFD）, and higher-order term optimized FFD method. The theoretical analyses and the impulse responses demonstrate that higher-order term optimized FFD method significantly extends the accurate propagation angle of the FFD method, which is useful to complex media with wider propagation angles.

金属矿集区深层结构高分辨率地震探测——以安徽铜陵金属矿为例

The reflection seismic prospecting technique is an important and a widely used method in the petroleum and coal surveying, and has been developed to a perfectly mature technique from the aspects of data acquisition, data processing to data interpretation. However, the metallic mine seismic prospecting, especially the high resolution seismic prospecting technique are being still in the course of studying and probing up to now. In this paper, the basic theory and the present situation of study on metallic mine seismic reflection are expatiated, the basic theory, the improving measure, the converging velocity and the ability on the integrating global optimization method are also illuminated in detail at first. Then the basic theory, the realization process and the practicing effects of the vector suppressing noise algorithm are also introduced. On the basis of studying of applying the integrating global optimization method to static correction and the vector suppressing noise algorithm, we elaborate processed the seismic data of Tongling metallic mine. We introduced the processing flow, the key steps and the processing effects. Basing on the processing results, we analyzed the major reflection characteristics, the geological interpretation results and the earth's crust top reflection structure and the space distribution status of Wutong set, the space shape of part lithological body and the contacting relations of horizonsunveiled.

A two-stage process with temperature-shift for enhanced anthocyanin production in strawberry cell suspension cultures

A two-stage process with temperature-shift has been developed to enhance the anthocyanin yield in suspension cultures of strawberry cells. The effect of the temperature-shift interval and the shift-time point was investigated for the optimization of this strategy. In this process, strawberry cells were grown at 30 degrees C (the optimum temperature for cell growth) for a certain period as the first stage, with the temperature shifted to a lower temperature for the second stage. In response to the temperature shift-down, anthocyanin synthesis was stimulated and a higher content could be achieved than that at both boundary temperatures but cell growth was suppressed. When the lower boundary temperature was decreased, cell growth was lowered and a delayed, sustained maximum anthocyanin content was achieved. Anthocyanin synthesis was strongly influenced by the shift-time point but cell growth was not. Consequently, the maximum anthocyanin content of 2.7 mg.g-fresh cell(-1) was obtained on day 9 by a temperature-shift from 30 degrees C, after 3-d culture, to 15 degrees C. The highest anthocyanin yield of 318 mg.L-1 on day 12 was achieved when the temperature was shifted from 30 degrees C, after 5-d culture, to 20 degrees C. For a global optimization of both the yield and productivity, the optimum anthocyanin yield and productivity of 272 mg.L-1 and 30.2 mg.L-1.d(-1) on day 9 were achieved by a two-stage culture with a temperature-shift from 30 degrees C after 3 d to 20 degrees C.

Optimization of Global Signal Networks for Island-Style FPGAs

We present a staggered buffer connection method that provides flexibility for buffer insertion while designing global signal networks using the tile-based FPGA design methodology. An exhaustive algorithm is used to analyze the trade-off between area and speed of the global signal networks for this staggered buffer insertion scheme, and the criterion for determining the design parameters is presented. The comparative analytic result shows that the methods in this paper are proven to be more efficient for FPGAs with a large array size.

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

Retention modeling and optimization of pH value and solvent composition in HPLC using back-propagation neural networks and uniform design

A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for both basic and acidic samples.

A spatial sampling optimization package using MSN theory

The density and distribution of spatial samples heavily affect the precision and reliability of estimated population attributes. An optimization method based on Mean of Surface with Nonhomogeneity (MSN) theory has been developed into a computer package with the purpose of improving accuracy in the global estimation of some spatial properties, given a spatial sample distributed over a heterogeneous surface; and in return, for a given variance of estimation, the program can export both the optimal number of sample units needed and their appropriate distribution within a specified research area. (C) 2010 Elsevier Ltd. All rights reserved.